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AI3SD Video: Prediction in organometallic catalysis – a challenge for computational chemistry

AI3SD Video: Prediction in organometallic catalysis – a challenge for computational chemistry
AI3SD Video: Prediction in organometallic catalysis – a challenge for computational chemistry
Computational results are now routinely used to contribute to the interpretation of experimental data, including for the confirmation of mechanistic postulates, but their contribution to substantial predictions made before experiments remains the exception [1], at least in the area of organometallic catalysis. More effective use of what we know about chemical reactions, regardless of whether the information was generated from experiment or calculation, will clearly play a role in moving towards this kind of ab initio prediction in this field. Here the adoption of statistics and data science into the chemical sciences are proving crucial and we have built large databases of parameters characterising ligand and complex properties in a range of different environments [2-6]. In this session, I will use examples drawn from our recent work, including the early stages of our development of a reactivity database, to illustrate this approach and discuss why organometallic catalysis is such a challenging yet rewarding area for prediction.
Website: https://feygroupchem.wordpress.com/

References:
1. J. Jover, N. Fey, Chem. Asian J., 9 (2014), 1714-1723; D. J. Durand, N. Fey, Chem. Rev., 119 (2019), 6561-6594.
2. A. Lai, J. Clifton, P. L. Diaconescu, N. Fey, Chem. Commun., 55 (2019), 7021-7024.
3. O. J. S. Pickup, I. Khazal, E. J. Smith, A. C. Whitwood, J. M. Lynam, K. Bolaky, T. C.
King, B. W. Rawe, N. Fey, Organometallics, 33 (2014), 1751-1791.
4. J. Jover, N. Fey, J. N. Harvey, G. C. Lloyd-Jones, A. G. Orpen, G. J. J. Owen-Smith, P.
Murray, D. R. J. Hose, R. Osborne, M. Purdie, Organometallics, 29 (2010), 6245-6258.
5. J. Jover, N. Fey, J. N. Harvey, G. C. Lloyd-Jones, A. G. Orpen, G. J. J. Owen-Smith, P.
Murray, D. R. J. Hose, R. Osborne, M. Purdie, Organometallics, 31 (2012), 5302-5306.
6. A. I. Green, C. P. Tinworth, S. Warriner, A. Nelson, N. Fey, Chem. Eur. J. 2020, Accepted Article, DOI: 10.1002/chem.202003801.
AI, AI3SD Event, Artificial Intelligence, Chemical Tomography, Chemistry, Machine Intelligence, Machine Learning, ML, Molecules Discovery, Prediction, Scientific Discovery
Fey, Natalie
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Kanza, Samantha
b73bcf34-3ff8-4691-bd09-aa657dcff420
Frey, Jeremy G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Niranjan, Mahesan
5cbaeea8-7288-4b55-a89c-c43d212ddd4f
Hooper, Victoria
af1a99f1-7848-4d5c-a4b5-615888838d84
Fey, Natalie
2888311d-048c-4a2f-aaa1-4c8e558c61b5
Kanza, Samantha
b73bcf34-3ff8-4691-bd09-aa657dcff420
Frey, Jeremy G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Niranjan, Mahesan
5cbaeea8-7288-4b55-a89c-c43d212ddd4f
Hooper, Victoria
af1a99f1-7848-4d5c-a4b5-615888838d84

Fey, Natalie (2020) AI3SD Video: Prediction in organometallic catalysis – a challenge for computational chemistry. Kanza, Samantha, Frey, Jeremy G., Niranjan, Mahesan and Hooper, Victoria (eds.) AI3SD Winter Seminar Series, , Online. 18 Nov 2020 - 21 Apr 2021 . (doi:10.5258/SOTON/P0093).

Record type: Conference or Workshop Item (Other)

Abstract

Computational results are now routinely used to contribute to the interpretation of experimental data, including for the confirmation of mechanistic postulates, but their contribution to substantial predictions made before experiments remains the exception [1], at least in the area of organometallic catalysis. More effective use of what we know about chemical reactions, regardless of whether the information was generated from experiment or calculation, will clearly play a role in moving towards this kind of ab initio prediction in this field. Here the adoption of statistics and data science into the chemical sciences are proving crucial and we have built large databases of parameters characterising ligand and complex properties in a range of different environments [2-6]. In this session, I will use examples drawn from our recent work, including the early stages of our development of a reactivity database, to illustrate this approach and discuss why organometallic catalysis is such a challenging yet rewarding area for prediction.
Website: https://feygroupchem.wordpress.com/

References:
1. J. Jover, N. Fey, Chem. Asian J., 9 (2014), 1714-1723; D. J. Durand, N. Fey, Chem. Rev., 119 (2019), 6561-6594.
2. A. Lai, J. Clifton, P. L. Diaconescu, N. Fey, Chem. Commun., 55 (2019), 7021-7024.
3. O. J. S. Pickup, I. Khazal, E. J. Smith, A. C. Whitwood, J. M. Lynam, K. Bolaky, T. C.
King, B. W. Rawe, N. Fey, Organometallics, 33 (2014), 1751-1791.
4. J. Jover, N. Fey, J. N. Harvey, G. C. Lloyd-Jones, A. G. Orpen, G. J. J. Owen-Smith, P.
Murray, D. R. J. Hose, R. Osborne, M. Purdie, Organometallics, 29 (2010), 6245-6258.
5. J. Jover, N. Fey, J. N. Harvey, G. C. Lloyd-Jones, A. G. Orpen, G. J. J. Owen-Smith, P.
Murray, D. R. J. Hose, R. Osborne, M. Purdie, Organometallics, 31 (2012), 5302-5306.
6. A. I. Green, C. P. Tinworth, S. Warriner, A. Nelson, N. Fey, Chem. Eur. J. 2020, Accepted Article, DOI: 10.1002/chem.202003801.

Video
AI3SD-Winter-Seminar-Series-Experiments-NatalieFey - Version of Record
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More information

Published date: 16 December 2020
Additional Information: I was born in Frechen, Germany, but have lived and worked in the UK for quite a while now. I obtained my BSc in Chemistry and Economics from Keele University (UK), and stayed on to work with Jim Howell and Paul Yates towards a PhD (completed in 2001). After postdoctoral research with Rob Deeth at the University of Warwick until 2003, I worked as a postdoc on projects with Guy Orpen, Jeremy Harvey and Guy Lloyd-Jones at the University of Bristol before gaining an EPSRC Advanced Research Fellowship (October 2007). My independent research at Bristol is in computational inorganic chemistry and involves mechanistic studies of catalysis and the development of knowledge bases. I was appointed to a temporary lectureship in 2015, made permanent in 2017, and promoted to senior lecturer in 2018. I’m the programme director for Chemistry with Scientific Computing and the Deputy Director of Bristol Scientific Computing.
Venue - Dates: AI3SD Winter Seminar Series, , Online, 2020-11-18 - 2021-04-21
Keywords: AI, AI3SD Event, Artificial Intelligence, Chemical Tomography, Chemistry, Machine Intelligence, Machine Learning, ML, Molecules Discovery, Prediction, Scientific Discovery

Identifiers

Local EPrints ID: 448981
URI: http://eprints.soton.ac.uk/id/eprint/448981
PURE UUID: 79417518-d612-4d7b-93e8-22142eeb3f2c
ORCID for Samantha Kanza: ORCID iD orcid.org/0000-0002-4831-9489
ORCID for Jeremy G. Frey: ORCID iD orcid.org/0000-0003-0842-4302

Catalogue record

Date deposited: 12 May 2021 16:38
Last modified: 13 May 2021 01:59

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Contributors

Author: Natalie Fey
Editor: Samantha Kanza ORCID iD
Editor: Jeremy G. Frey ORCID iD
Editor: Mahesan Niranjan
Editor: Victoria Hooper

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